About this Document

Using the html file

On the left is a floating table of contents for navigating between major sections of output:

Exploration and QA/QC
Summary bar charts
Univariate analyses
Multivariate analyses

Within each major section, content is split into tabs that are spread horizontally across the screen. By default, the About tab for each section is showing. Click on any tab to see specifics.

General notes about notation, data inclusion, and reserve choices

If a species was identified as being of interest, and the category that species belongs to (e.g. H-Halophyte / B-Brackish / Unvegetated category) was also identified as being of interest, the species takes precedent and the category represents only the other species in that category. The species itself is not represented in both.
If a species was identified as belonging to an “Other layer” - something like canopy wrack, or water when whatever is below the water is also measured - it was removed before any of these analyses (including exploratory graphics).

Exploration and QA/QC

About

This section contains tables and graphs, in separate tabs.

To detect errors in data sets, the information in this section should be reviewed by Reserve data practitioners. These results are meant to help you find issues that need to be corrected in the raw data, and decide whether plots or data should be removed from analyses (e.g., “off season” surveys, plots no longer monitored, restoration sites).

Ask yourself:

Do you see the correct number of sampling events per year? If not, what is missing or extra? This implies a correction needs to be made in the raw data file.
Do you see the correct number of plots per site?
Are species names spelled correctly? Are there any close variants or duplicates (e.g., capital vs lowercase, misspelled)?
General percent cover in plots - is anything unusual (e.g., over 100% when standardized, sudden drops or spikes in species)?

Missing/Removed Data

Plots/dates without samples

There were 1 rows with no data. These rows were removed from the dataset before further processing. If rows were removed, relevant information is in a table below.

Plots without enough samples

If monitoring plots did not have data in at least 3 separate years, they were removed from the dataset before statistical analyses. These plots do appear in the plots and information in the Exploration/QAQC and Summary Bar Chart sections of this document, but were removed before Univariate and Multivariate analyses.

In this dataset, there were 1 such plots removed. If plots were removed, relevant information is in a table below.

Data flagged suspect or reject

There were 0 data points that were removed due to QA/QC flags. If data points were removed, relevant information is in a table below.

Sampling Info

Samples per year

# samples per year, by site
Site	2010	2011	2013	2014	2016	2017	2018	2019	2020	2021	2022
BC	29	30	30	30	30	30	30	30	30	30	30
GBF	39	39	39	39	39	39	39	39	39	39	39
SP	43	44	44	45	45	45	45	45	45	45	45

# samples per year, by vegetation zone
Vegetation_Zone	2010	2011	2013	2014	2016	2017	2018	2019	2020	2021	2022
L-Low Marsh	21	22	22	22	22	22	22	22	22	22	22
T-Transition	32	32	32	32	32	32	32	32	32	32	32
H-High Marsh	42	42	42	42	42	42	42	42	42	42	42
UE-Upland Edge	16	17	17	18	18	18	18	18	18	18	18

Species

Plots and Zones

Make sure the colors below correctly represent which Vegetation Zones your plots belong to. If something looks wrong, it needs to be corrected in the ‘Station_Table’ tab of your data workbook.

Time-series - Species

By Zone

All plots combined

EMI

EMI, Ecotone Migration Index, is the proportional cover of species/covers or species/cover groupings that are expected to increase within a vegetation zone as sea level rises. These species were identified by reserve staff, for each zone, in the ‘veg-specs.xlsx’ file.

Species considered to be ‘migrators’ within each zone are denoted by ‘x’ in the following table:

Species	L-Low Marsh	T-Transition	H-High Marsh	UE-Upland Edge
Algae	X	X	X	X
Ascophyllum nodosum	X	X	X	X
Ascophyllum nodosum var. scorpioides	X	X	X	X
Bare	X	X	X	X
Fucus spiralis	X	X	X	X
Fucus spp.	X	X	X	X
Fucus vesiculosus	X	X	X	X
Gracilaria spp.	X	X	X	X
Ulva lactuca	X	X	X	X
Ulva spp.	X	X	X	X
Vaucheria spp.	X	X	X	X
Water	X	X	X	X
Spartina alterniflora		X	X	X
Agalinis maritima				X
Agrostis stolonifera				X
Amaranthus cannabinus				X
Ammophila breviligulata				X
Anthoxanthum nitens				X
Asparagus officinalis				X
Atriplex patula				X
Baccharis halimifolia				X
Bolboschoenus maritimus				X
Bolboschoenus robustus				X
Calystegia sepium				X
Carex hormathodes				X
Carex paleacea				X
Cuscuta gronovii				X
Cuscuta spp.				X
Distichlis spicata				X
Eleocharis parvula				X
Elymus virginicus				X
Euthamia graminifolia				X
Festuca rubra				X
Galium lanceolatum				X
Galium palustre				X
Hibiscus moscheutos				X
Hordeum spp.				X
Iva frutescens				X
Juncus articulatus				X
Juncus balticus				X
Juncus gerardii				X
Juncus spp.				X
Limonium carolinianum				X
Lysimachia maritima				X
Lythrum salicaria				X
Myrica gale				X
Panicum virgatum				X
Phragmites australis				X
Phragmites australis ssp. americanus				X
Plantago maritima				X
Pluchea odorata				X
Polygonum ramosissimum				X
Potentilla anserina				X
Prunus maritima				X
Puccinellia maritima				X
Rosa multiflora				X
Rosa rugosa				X
Ruppia maritima				X
Salicornia depressa				X
Salicornia maritima				X
Salicornia spp.				X
Schoenoplectus americanus				X
Schoenoplectus pungens				X
Schoenoplectus spp.				X
Scirpus cyperinus				X
Setaria spp.				X
Solidago sempervirens				X
Spartina X caespitosa				X
Spartina alterniflora (short)				X
Spartina patens				X
Spartina patens hybrid				X
Spartina pectinata				X
Spergularia salina				X
Suaeda linearis				X
Suaeda maritima				X
Symphyotrichum subulatum				X
Symphyotrichum tenuifolium				X
Thinopyrum pungens				X
Toxicodendron radicans				X
Triglochin maritima				X
Typha angustifolia				X

Summary Bar Charts

About

This section contains summary graphics. The color palettes are generated via the khroma R package and were developed to be colorblind-friendly.

These summary figures tell a graphical story about current conditions and trends through time. There are two types of figure:

Averaged stacked bar charts - show the relative distribution of species and cover classes and how these relationships change over time.
- Charts have been created at the Site, Zone, and Site x Zone levels.
- Chart categories feature dominant species or species groups as identified by the Reserve in the “veg-specs.xlsx” file, “Analysis_Specs” sheet.
Spatial stacked bar charts - show the relative distribution of species and cover classes as above, but for each plot. These charts are laid out spatially by site. For ease of interpretation, only 4 evenly-spaced time points are used along the x-axis in each chart.

Questions addressed

Which species characterize each site and marsh zone?
How do relative abundances of species/groups fluctuate among years and is there a visual trend with time (e.g., corresponds to severe events, storms, staff turnover)?
For QA/QC purposes, does the data make sense?

Averaged: By Veg Zone

User-chosen species

The species/groups identified by the Reserve for these graphs are (in order):

Unvegetated category
A-Algae
Spartina alterniflora
Spartina patens
H-Halophyte
B-Brackish
F-Freshwater
U-Upland

And so the groups appearing in the plots should be (alphabetically):

A-Algae
B-Brackish
F-Freshwater
H-Halophyte
Spartina alterniflora
Spartina patens
U-Upland
Unvegetated category
Other

Top 3 species by mean cover across the entire dataset

These were automatically calculated as the species having the highest mean cover, across all plots and dates.

Averaged: By Site

User-chosen species

Top 3 species by mean cover across the entire dataset

Averaged: Zone within Site

User-chosen species

Top 3 species by mean cover across the entire dataset

Spatial

One spatial graph was generated for each Site. This can be changed between the options of Site and Transect in the “More_Options” sheet of the “veg-specs.xlsx” file.

Each panel on the graphs represents an individual vegetation plot, showing 4 evenly spaced-through-time samples, of the species choices from the “Analysis_Specs” sheet of the “veg-specs.xlsx” file.

Plots without associated spatial locations will not be included in these graphics.

User-chosen species

Top 3 species by mean cover across the entire dataset

Univariate Analyses

About

A tab will be generated for results of each response variable. The response variables consist of each of the (up to) 4 response variables identified in the Analysis Specs spreadsheet, (up to) 2 custom metrics identified in the Analysis Specs spreadsheet, EMI (Ecotone Migration Index), Species Richness, and Shannon-Weiner Diversity Index. You will see the same tables and graphics for each.

Questions addressed

Are there shifts in key vegetation species/groups over time?
Do these shifts vary by vegetation zone?
Follow-up: Where is the plant community changing (which plots) and what characteristics do those areas have in common (e.g. site, zone, distance from water, elevation)?

Statistical Model

The main statistical model used is a linear mixed model, via lme4::lmer(), with the form y ~ Vegetation Zone + Time + Zone*Time + 1|Plot, where y is the response variable given in the tab, and each individual plot has a random intercept.

If only one vegetation zone is present in the data file, Vegetation Zone is removed and the statistical model is simplified to y ~ Time + 1|Plot.

Reserve-identified response variables:

The reserve-identified univariate response variables are:

Unvegetated category
Spartina alterniflora
Spartina patens
H-Halophyte

Custom Metrics

Any custom metrics specified in the ‘Analysis_Specs’ sheet of the ‘veg-specs.xlsx’ file are calculated here, for inclusion in univariate analyses.

If you do not see a tab for a metric you believe you defined, look just below these bullet points to see if there are error messages showing up in little boxes that are different from other text - these may be helpful in troubleshooting. There are a few likely reasons for problems:

Make sure the species or groupings you want to use are in the ‘Species_Names’ sheet of your data file.
Make sure any species or groupings are enclosed in backticks. Backticks are not the same as single quotes or apostrophes. To make a backtick, use the key to the left of the number 1 on your keyboard.
Make sure species and groups are spelled correctly.
Make sure species and groups are capitalized correctly (“correctly” = however it is capitalized in the ‘Species_Names’ sheet of the data file). e.g., if you want to include ‘live vegetation’ in your metric, check the Species_Names sheet of the data file and you will see it is ‘Live vegetation’. If you capitalize it any other way, R will not recognize it and thus will not calculate the metric.
Check your math - if you are using division, try adding 1 to the denominator to avoid the possibility of dividing by 0. Make sure you have parentheses around terms that should be evaluated together.

## Created new column: A-Algae

EMI

See the ‘EMI’ tab in the ‘Exploratory and QA/QC’ section of this document for a table of species considered to be ‘ecotone migrators’ for each zone.

The current file contains multiple vegetation zones, and vegetation zone will be one of the predictors in the statistical model. Results are presented for each vegetation zone independently because the marginal effects are of interest to the project team. However, be careful interpreting zone-wise results if the interaction term (Years_sinceStart:Vegetation_Zone) is not significant (p > 0.05).

Numerical effects

EMI - Type III Analysis of Variance Table, using Kenward-Rogers method
	Sum Sq	Mean Sq	NumDF	DenDF	F value	Pr(>F)
Years_sinceStart	2.5850	2.5850	1	1130.02	88.17	0.0000
Vegetation_Zone	2.7803	0.9268	3	155.09	31.61	0.0000
Years_sinceStart:Vegetation_Zone	0.2823	0.0941	3	1129.83	3.21	0.0224

EMI - Estimated marginal slopes (change per year for each zone)
Veg Zone	Trend (per year)	SE	CI lower	CI upper	t	df	p.val
L-Low Marsh	0.0133	0.0029	0.008	0.019	4.6	1129.9	0.0000
T-Transition	0.0184	0.0024	0.014	0.023	7.8	1129.0	0.0000
H-High Marsh	0.0092	0.0021	0.005	0.013	4.4	1129.0	0.0000
UE-Upland Edge	0.0096	0.0032	0.003	0.016	3.0	1131.1	0.0032

Marginal R^2 (R2m) represents the variance explained by the fixed effects. Conditional R^2 (R2c) represents the variance explained by the entire model, which includes both fixed and random effects.

EMI - Margn’l and Cond’l R^2 values
R2m	R2c
0.439	0.755

Graphs

Contrasts plot

If the interaction between vegetation zone and time was significant (p < 0.05), letters are used to represent groups of slopes that are not significantly different (via pairwise comparisons). If the interaction was not significant, this plot represents the marginal slopes but no letters are used.

Some notes from the function. Kenward-Roger method used to estimate denominator degrees of freedom. Confidence level used: 0.95. p-value adjustment: Tukey. alpha = 0.05.

“If two or more means share the same grouping symbol, then we cannot show them to be different. But we also did not show them to be the same.”

Same plot, but x-axis goes from lowest to highest zone.

Richness

Species Richness, calculated on all non-abiotic, non-dead, and non-overstory columns; using the vegan package.

Numerical effects

Richness - Type III Analysis of Variance Table, using Kenward-Rogers method
	Sum Sq	Mean Sq	NumDF	DenDF	F value	Pr(>F)
Years_sinceStart	32.884	32.8840	1	1129.82	22.17	0.0000
Vegetation_Zone	140.197	46.7323	3	145.33	31.50	0.0000
Years_sinceStart:Vegetation_Zone	30.113	10.0377	3	1129.67	6.77	0.0002

Richness - Estimated marginal slopes (change per year for each zone)
Veg Zone	Trend (per year)	SE	CI lower	CI upper	t	df	p.val
L-Low Marsh	0.0133	0.0207	-0.027	0.054	0.6	1129.7	0.5217
T-Transition	-0.0861	0.0168	-0.119	-0.053	-5.1	1129.0	0.0000
H-High Marsh	-0.0193	0.0147	-0.048	0.010	-1.3	1129.0	0.1894
UE-Upland Edge	-0.0878	0.0231	-0.133	-0.043	-3.8	1130.7	0.0001

Marginal R^2 (R2m) represents the variance explained by the fixed effects. Conditional R^2 (R2c) represents the variance explained by the entire model, which includes both fixed and random effects.

Richness - Margn’l and Cond’l R^2 values
R2m	R2c
0.347	0.754

Graphs

Contrasts plot

Some notes from the function. Kenward-Roger method used to estimate denominator degrees of freedom. Confidence level used: 0.95. p-value adjustment: Tukey. alpha = 0.05.

“If two or more means share the same grouping symbol, then we cannot show them to be different. But we also did not show them to be the same.”

Same plot, but x-axis goes from lowest to highest zone.

Diversity

Shannon-Weiner Diversity index, calculated on all non-abiotic, non-dead, and non-overstory columns; using the vegan package.

Numerical effects

SWdiv - Type III Analysis of Variance Table, using Kenward-Rogers method
	Sum Sq	Mean Sq	NumDF	DenDF	F value
Years_sinceStart	2.0755	2.0755	1	1129.81	26.69
Vegetation_Zone	5.5518	1.8506	3	144.83	23.79
Years_sinceStart:Vegetation_Zone	2.5077	0.8359	3	1129.66	10.75

SWdiv - Estimated marginal slopes (change per year for each zone)
Veg Zone	Trend (per year)	SE	CI lower	CI upper	t	df	p.val
L-Low Marsh	0.0032	0.0047	-0.006	0.013	0.7	1129.7	0.4951
T-Transition	-0.0277	0.0039	-0.035	-0.020	-7.2	1129.0	0.0000
H-High Marsh	-0.0046	0.0034	-0.011	0.002	-1.4	1129.0	0.1732
UE-Upland Edge	-0.0162	0.0053	-0.027	-0.006	-3.1	1130.6	0.0022

Marginal R^2 (R2m) represents the variance explained by the fixed effects. Conditional R^2 (R2c) represents the variance explained by the entire model, which includes both fixed and random effects.

SWdiv - Margn’l and Cond’l R^2 values
R2m	R2c
0.3	0.739

Graphs

Contrasts plot

Some notes from the function. Kenward-Roger method used to estimate denominator degrees of freedom. Confidence level used: 0.95. p-value adjustment: Tukey. alpha = 0.05.

“If two or more means share the same grouping symbol, then we cannot show them to be different. But we also did not show them to be the same.”

Same plot, but x-axis goes from lowest to highest zone.

Unvegetated category

Numerical effects

Unvegetated category - Type III Analysis of Variance Table, using Kenward-Rogers method
	Sum Sq	Mean Sq	NumDF	DenDF	F value	Pr(>F)
Years_sinceStart	1629.731	1629.731	1	1130.31	5.04	0.0249
Vegetation_Zone	4720.645	1573.549	3	169.57	4.87	0.0028
Years_sinceStart:Vegetation_Zone	3405.042	1135.014	3	1130.06	3.51	0.0148

Unvegetated category - Estimated marginal slopes (change per year for each zone)
Veg Zone	Trend (per year)	SE	CI lower	CI upper	t	df	p.val
L-Low Marsh	1.0755	0.3055	0.476	1.675	3.5	1130.2	0.0004
T-Transition	-0.0083	0.2487	-0.496	0.480	0.0	1129.0	0.9735
H-High Marsh	-0.0732	0.2170	-0.499	0.353	-0.3	1129.0	0.7358
UE-Upland Edge	0.2727	0.3406	-0.396	0.941	0.8	1131.6	0.4236

Marginal R^2 (R2m) represents the variance explained by the fixed effects. Conditional R^2 (R2c) represents the variance explained by the entire model, which includes both fixed and random effects.

Unvegetated category - Margn’l and Cond’l R^2 values
R2m	R2c
0.129	0.56

Graphs

Contrasts plot

Some notes from the function. Kenward-Roger method used to estimate denominator degrees of freedom. Confidence level used: 0.95. p-value adjustment: Tukey. alpha = 0.05.

“If two or more means share the same grouping symbol, then we cannot show them to be different. But we also did not show them to be the same.”

Same plot, but x-axis goes from lowest to highest zone.

Spartina alterniflora

Numerical effects

Spartina alterniflora - Type III Analysis of Variance Table, using Kenward-Rogers method
	Sum Sq	Mean Sq	NumDF	DenDF	F value	Pr(>F)
Years_sinceStart	405.6369	405.6369	1	1130.18	1.77	0.1832
Vegetation_Zone	42582.9588	14194.3196	3	163.11	62.06	0.0000
Years_sinceStart:Vegetation_Zone	15343.8677	5114.6226	3	1129.96	22.36	0.0000

Spartina alterniflora - Estimated marginal slopes (change per year for each zone)
Veg Zone	Trend (per year)	SE	CI lower	CI upper	t	df	p.val
L-Low Marsh	-1.2837	0.2570	-1.788	-0.780	-5.0	1130.0	0.0000
T-Transition	1.3771	0.2092	0.967	1.787	6.6	1129.0	0.0000
H-High Marsh	0.5387	0.1825	0.181	0.897	3.0	1129.0	0.0032
UE-Upland Edge	0.0000	0.2865	-0.562	0.562	0.0	1131.4	1.0000

Marginal R^2 (R2m) represents the variance explained by the fixed effects. Conditional R^2 (R2c) represents the variance explained by the entire model, which includes both fixed and random effects.

Spartina alterniflora - Margn’l and Cond’l R^2 values
R2m	R2c
0.524	0.773

Graphs

Contrasts plot

Some notes from the function. Kenward-Roger method used to estimate denominator degrees of freedom. Confidence level used: 0.95. p-value adjustment: Tukey. alpha = 0.05.

“If two or more means share the same grouping symbol, then we cannot show them to be different. But we also did not show them to be the same.”

Same plot, but x-axis goes from lowest to highest zone.

Spartina patens

Numerical effects

Spartina patens - Type III Analysis of Variance Table, using Kenward-Rogers method
	Sum Sq	Mean Sq	NumDF	DenDF	F value	Pr(>F)
Years_sinceStart	1628.053	1628.053	1	1129.47	12.30	0.0005
Vegetation_Zone	4823.244	1607.748	3	129.64	12.14	0.0000
Years_sinceStart:Vegetation_Zone	1820.403	606.801	3	1129.38	4.58	0.0034

Spartina patens - Estimated marginal slopes (change per year for each zone)
Veg Zone	Trend (per year)	SE	CI lower	CI upper	t	df	p.val
L-Low Marsh	-0.0257	0.1955	-0.409	0.358	-0.1	1129.4	0.8955
T-Transition	-0.8309	0.1591	-1.143	-0.519	-5.2	1129.0	0.0000
H-High Marsh	-0.3702	0.1389	-0.643	-0.098	-2.7	1129.0	0.0078
UE-Upland Edge	-0.0395	0.2181	-0.467	0.388	-0.2	1130.0	0.8563

Marginal R^2 (R2m) represents the variance explained by the fixed effects. Conditional R^2 (R2c) represents the variance explained by the entire model, which includes both fixed and random effects.

Spartina patens - Margn’l and Cond’l R^2 values
R2m	R2c
0.192	0.796

Graphs

Contrasts plot

Some notes from the function. Kenward-Roger method used to estimate denominator degrees of freedom. Confidence level used: 0.95. p-value adjustment: Tukey. alpha = 0.05.

“If two or more means share the same grouping symbol, then we cannot show them to be different. But we also did not show them to be the same.”

Same plot, but x-axis goes from lowest to highest zone.

H-Halophyte

Numerical effects

H-Halophyte - Type III Analysis of Variance Table, using Kenward-Rogers method
	Sum Sq	Mean Sq	NumDF	DenDF	F value	Pr(>F)
Years_sinceStart	11.4839	11.4839	1	1129.57	0.08	0.7816
Vegetation_Zone	6866.3541	2288.7847	3	133.87	15.32	0.0000
Years_sinceStart:Vegetation_Zone	1182.2268	394.0756	3	1129.46	2.64	0.0484

H-Halophyte - Estimated marginal slopes (change per year for each zone)
Veg Zone	Trend (per year)	SE	CI lower	CI upper	t	df	p.val
L-Low Marsh	-0.0796	0.2077	-0.487	0.328	-0.4	1129.5	0.7018
T-Transition	-0.4169	0.1691	-0.749	-0.085	-2.5	1129.0	0.0138
H-High Marsh	0.0894	0.1475	-0.200	0.379	0.6	1129.0	0.5447
UE-Upland Edge	0.3007	0.2316	-0.154	0.755	1.3	1130.2	0.1944

Marginal R^2 (R2m) represents the variance explained by the fixed effects. Conditional R^2 (R2c) represents the variance explained by the entire model, which includes both fixed and random effects.

H-Halophyte - Margn’l and Cond’l R^2 values
R2m	R2c
0.264	0.786

Graphs

Contrasts plot

Some notes from the function. Kenward-Roger method used to estimate denominator degrees of freedom. Confidence level used: 0.95. p-value adjustment: Tukey. alpha = 0.05.

“If two or more means share the same grouping symbol, then we cannot show them to be different. But we also did not show them to be the same.”

Same plot, but x-axis goes from lowest to highest zone.

AlgaeEtc.

This custom metric was calculated using the following formula:

(A-Algae + Spartina alterniflora + Salicornia depressa + Bare + Wrack) / Total

Numerical effects

AlgaeEtc. - Type III Analysis of Variance Table, using Kenward-Rogers method
	Sum Sq	Mean Sq	NumDF	DenDF	F value
Years_sinceStart	0.5883	0.5883	1	1130.00	23.77
Vegetation_Zone	6.7862	2.2621	3	153.81	91.39
Years_sinceStart:Vegetation_Zone	0.7896	0.2632	3	1129.81	10.63

AlgaeEtc. - Estimated marginal slopes (change per year for each zone)
Veg Zone	Trend (per year)	SE	CI lower	CI upper	t	df	p.val
L-Low Marsh	0.0016	0.0027	-0.004	0.007	0.6	1129.9	0.5561
T-Transition	0.0170	0.0022	0.013	0.021	7.8	1129.0	0.0000
H-High Marsh	0.0061	0.0019	0.002	0.010	3.2	1129.0	0.0013
UE-Upland Edge	-0.0006	0.0030	-0.006	0.005	-0.2	1131.0	0.8300

Marginal R^2 (R2m) represents the variance explained by the fixed effects. Conditional R^2 (R2c) represents the variance explained by the entire model, which includes both fixed and random effects.

AlgaeEtc. - Margn’l and Cond’l R^2 values
R2m	R2c
0.654	0.852

Graphs

Contrasts plot

Some notes from the function. Kenward-Roger method used to estimate denominator degrees of freedom. Confidence level used: 0.95. p-value adjustment: Tukey. alpha = 0.05.

“If two or more means share the same grouping symbol, then we cannot show them to be different. But we also did not show them to be the same.”

Same plot, but x-axis goes from lowest to highest zone.

Sppa.Disp.Juge

This custom metric was calculated using the following formula:

Spartina patens + Distichlis spicata + Juncus gerardii

Numerical effects

Sppa.Disp.Juge - Type III Analysis of Variance Table, using Kenward-Rogers method
	Sum Sq	Mean Sq	NumDF	DenDF	F value	Pr(>F)
Years_sinceStart	1132.303	1132.303	1	1129.56	6.16	0.0132
Vegetation_Zone	17343.311	5781.104	3	133.56	31.46	0.0000
Years_sinceStart:Vegetation_Zone	5247.947	1749.315	3	1129.46	9.52	0.0000

Sppa.Disp.Juge - Estimated marginal slopes (change per year for each zone)
Veg Zone	Trend (per year)	SE	CI lower	CI upper	t	df	p.val
L-Low Marsh	-0.0346	0.2304	-0.487	0.417	-0.2	1129.5	0.8807
T-Transition	-1.1477	0.1875	-1.516	-0.780	-6.1	1129.0	0.0000
H-High Marsh	0.0545	0.1636	-0.266	0.375	0.3	1129.0	0.7391
UE-Upland Edge	0.0717	0.2569	-0.432	0.576	0.3	1130.1	0.7801

Marginal R^2 (R2m) represents the variance explained by the fixed effects. Conditional R^2 (R2c) represents the variance explained by the entire model, which includes both fixed and random effects.

Sppa.Disp.Juge - Margn’l and Cond’l R^2 values
R2m	R2c
0.421	0.833

Graphs

Contrasts plot

Some notes from the function. Kenward-Roger method used to estimate denominator degrees of freedom. Confidence level used: 0.95. p-value adjustment: Tukey. alpha = 0.05.

“If two or more means share the same grouping symbol, then we cannot show them to be different. But we also did not show them to be the same.”

Same plot, but x-axis goes from lowest to highest zone.

Multivariate Analyses

About

These tabs are the multivariate analyses.

In this section, we use multivariate techniques to ordination to visualize and analyze plant community change through plot-level cover data across marsh zones.

Questions and statistical methods

Are there shifts in the vegetation community (as defined by the entire percent-cover matrix) over time? Do these shifts vary by vegetation zone?
- addressed with PERMANOVA, comparing first year of monitoring to the ‘last’ (most recent) year of monitoring.
- the first and last year of monitoring at a specific vegetation plot should be considered together. To do this, permutations were restricted to allow swapping of time point within a vegetation plot, but keep both time points of a plot together as plots are permuted across vegetation zones. Unfortunately these restricted permutations do not account for the repeated measures within a plot. Ideally we could use a random effect, as in the univariate models. At this point such a model for PERMANOVA is not possible in R.
- if the above test indicated that differences in time between vegetation zones were significant or nearly so (p <= 0.10), the species matrix was split by Vegetation Zone. A PERMANOVA was run for each vegetation zone, again with restricted permutations to allow only permutation of tiem point within vegetation plot.
Which species/groups contribute most to these shifts?
- addressed using SIMPER, comparing first and last year of monitoring data within each zone. SIMPER is used to follow up on vegetation zones where the p-value for the PERMANOVA was <= 0.2.
Where is the plant community changing, and what characteristics do those areas have in common (e.g. site, zone, distance from water, elevation)?
- visualized via NMDS.

Reserve output choices

The following species/groups were identified by the reserve as important loading factors to display on NMDS outputs.

Sometimes these species do not appear on the plots; usually that is because all data points for that species were 0 or very close to it.

Up to 8 species/groups could be identified specifically in outputs of these multivariate analyses. Reserve choices are:

Unvegetated category
A-Algae
Spartina alterniflora
Spartina patens
H-Halophyte
B-Brackish
F-Freshwater
U-Upland

Characteristics of multivariate data frame

Years in ‘Start’ and ‘End’ time groups for each Vegetation Zone. Number in parentheses is number of samples.
Vegetation_Zone	Start	End
L-Low Marsh	2010 (20)	2022 (20)
T-Transition	2010 (32)	2022 (32)
H-High Marsh	2010 (42)	2022 (42)
UE-Upland Edge	2010 (16)	2022 (16)

Species/Groups included in response matrix

Bare
Dead
Other Unvegetated
Rock
Wood
Wrack
Acer rubrum
Achillea millefolium
Agalinis maritima
Agrostis stolonifera
Algae
Alnus spp.
Amaranthus cannabinus
Amelanchier canadensis
Ammophila breviligulata
Anthoxanthum nitens
Apios americana
Aquilegia canadensis
Arachis spp.
Aralia nudicaulis
Ascophyllum nodosum
Ascophyllum nodosum var. scorpioides
Asparagus officinalis
Athyrium filix-femina var. angustum
Atriplex patula
Baccharis halimifolia
Berberis thunbergii
Betula populifolia
Bidens spp.
Boehmeria cylindrica
Bolboschoenus maritimus
Bolboschoenus robustus
Calystegia sepium
Carex hormathodes
Carex paleacea
Carex pensylvanica
Carex spp.
Carex stricta
Carya ovata
Chelone glabra
Cinna arundinacea
Cuscuta gronovii
Cuscuta spp.
Cyperus spp.
Distichlis spicata
Drosera rotundifolia
Elaeagnus umbellata
Eleocharis parvula
Eleocharis rostellata
Eleocharis spp.
Elymus spp.
Elymus virginicus
Epilobium spp.
Equisetum fluviatile
Euthamia graminifolia
Fagus grandifolia
Fallopia convolvulus
Fallopia japonica var. japonica
Festuca rubra
Fucus spiralis
Fucus spp.
Fucus vesiculosus
Galium lanceolatum
Galium palustre
Geranium spp.
Gracilaria spp.
Hamamelis virginiana
Hibiscus moscheutos
Hordeum spp.
Hypericum perforatum
Ilex glabra
Ilex verticillata
Impatiens capensis
Iris spp.
Iris versicolor
Iva frutescens
Juncus articulatus
Juncus balticus
Juncus gerardii
Juncus spp.
Juniperus communis
Juniperus spp.
Juniperus virginiana
Lactuca canadensis
Lemna minor
Lepidium virginicum
Lichen
Limonium carolinianum
Lonicera japonica
Lonicera spp.
Lycopus virginicus
Lyonia ligustrina
Lysimachia maritima
Lysimachia quadrifolia
Lythrum salicaria
Lythrum spp.
Maianthemum canadense
Maianthemum racemosum ssp. racemosum
Mentha arvensis
Morella pensylvanica
Myosotis spp.
Myrica gale
Myrica spp.
Oenothera biennis
Onoclea sensibilis
Osmunda regalis
Osmundastrum cinnamomeum
Panicum virgatum
Parthenocissus quinquefolia
Persicaria sagittata
Phalaris arundinacea
Phragmites australis
Phragmites australis ssp. americanus
Picea spp.
Pinus rigida
Pinus strobus
Plantago maritima
Plantago major
Pluchea odorata
Poa nemoralis
Polygonum ramosissimum
Potentilla anserina
Prunus avium
Prunus maritima
Prunus serotina
Prunus virginiana
Pseudognaphalium obtusifolium
Pteridium aquilinum
Puccinellia maritima
Pyrus spp.
Quercus alba
Quercus bicolor
Quercus ilicifolia
Quercus rubra
Quercus spp.
Rhamnus cathartica
Rhamnus spp.
Rhododendron spp.
Rosa multiflora
Rosa palustris
Rosa rugosa
Rosa spp.
Rubus spp.
Rumex crispus
Ruppia maritima
Salicornia depressa
Salicornia maritima
Salicornia spp.
Salix spp.
Sambucus nigra
Schoenoplectus americanus
Schoenoplectus pungens
Schoenoplectus spp.
Scirpus atrovirens
Scirpus cyperinus
Scutellaria lateriflora
Setaria spp.
Smilax regelii
Smilax rotundifolia
Smilax spp.
Solanum dulcamara
Solidago rugosa
Solidago sempervirens
Solidago spp.
Sonchus oleraceus
Spartina alterniflora
Spartina alterniflora (short)
Spartina patens
Spartina patens hybrid
Spartina pectinata
Spartina X caespitosa
Spergularia salina
Sphagnum spp.
Spiraea alba
Spiraea alba var. latifolia
Spiraea spp.
Spiraea tomentosa
Suaeda linearis
Suaeda maritima
Symphyotrichum ericoides
Symphyotrichum novi-belgii
Symphyotrichum spp.
Symphyotrichum subulatum
Symphyotrichum tenuifolium
Symplocarpus foetidus
Teucrium canadense
Thalictrum dioicum
Thalictrum pubescens
Thelypteris noveboracensis
Thelypteris palustris
Thinopyrum pungens
Thinopyrum pycnanthum
Toxicodendron radicans
Triadenum virginicum
Trientalis borealis
Triglochin maritima
Typha angustifolia
Typha latifolia
Ulva lactuca
Ulva spp.
Vaccinium angustifolium
Vaccinium corymbosum
Vaucheria spp.
Viburnum dentatum
Vicia cracca
Viola cucullata
Unknown 1
Unknown 2
Unknown 3

PERMANOVA

Overall

H0: Community change (if any) between start and end is consistent across vegetation zones.

The interaction p-value (Vegetation_Zone:Time_group) is what to look at here:

If the interaction is significant, then something different happened through time in at least one vegetation zone. Do not interpret the main effects; proceed to the zone-wise tables below. If the interaction is significant or close to it (p <= 0.10), separate PERMANOVAs will be run for each vegetation zone to determine whether community change occurred in each zone separately.
If the interaction is not significant, look at the main effect of Time_group to determine whether, across all zones, the community was different at the end of monitoring than at the beginning.

Permutations have been restricted so that time points are only permuted within a vegetation plot, and both time points for a plot are permuted together across vegetation zones.

If only one vegetation zone is present in the data file, the overall PERMANOVA will be skipped; look in the zone-wise PERMANOVA section below for results.

Overall PERMANOVA results, terms treated sequentially
	Df	SumOfSqs	R2	F	Pr(>F)
Time_group	1	0.9464	0.0135	4.1105	0.002
Vegetation_Zone	3	18.8937	0.2701	27.3550	0.001
Time_group:Vegetation_Zone	3	1.2897	0.0184	1.8672	0.015
Residual	212	48.8083	0.6979
Total	219	69.9380	1.0000

Zone-wise

H0: No community difference between ‘start’ and ‘end’ within a vegetation zone.

Permutations have been restricted so time points are only permuted within a vegetation plot.

Summary of pairwise PERMANOVAs testing community difference between first and most recent years of monitoring
Vegetation Zone	R2	p.value	p.value_Bonferonni
L-Low Marsh	0.1309	0.010	0.040
T-Transition	0.0902	0.001	0.004
H-High Marsh	0.0137	0.284	1.000
UE-Upland Edge	0.0355	0.313	1.000

Check for homogeneity of dispersion

H0: No difference in dispersion between groups.

This is important to check because one of the assumptions of PERMANOVA is homogeneity of dispersion. Dispersion is the multivariate equivalent of variance. If this assumption is violated, caution should be used in interpreting PERMANOVA results.

The test used here is PERMDISP, implemented with the betadisper function of the vegan package.

Results of dispersion test, overall PERMANOVA
	Df	Sum Sq	Mean Sq	F	N.Perm	Pr(>F)
Groups	7	3.39	0.48	19.58	999	0.001
Residuals	212	5.24	0.02

If the PERMDISP indicated significant difference in dispersions, you should further investigate the following outputs:

Group	Mean Distance
L-Low Marsh; Start	0.204
L-Low Marsh; End	0.333
T-Transition; Start	0.418
T-Transition; End	0.269
H-High Marsh; Start	0.541
H-High Marsh; End	0.542
UE-Upland Edge; Start	0.547
UE-Upland Edge; End	0.501

Summary of dispersion test outputs for each zone
Vegetation Zone	Start.dispersion	End.dispersion	NumDf	DenDf	F.val	N.Perm	p.val
L-Low Marsh	0.205	0.335	1	38	7.3	999	0.008
T-Transition	0.418	0.266	1	62	9.6	999	0.003
H-High Marsh	0.541	0.542	1	82	0.0	999	0.959
UE-Upland Edge	0.547	0.502	1	30	1.3	999	0.282

Click to view plots of dispersion for each zone

SIMPER

SIMPER was run if:

Across all zones: the interaction term in the overall PERMANOVA was not significant (p > 0.05) and the main effect for time was significant or close to it (p <= 0.2).
Zone-wise: the interaction term in the overall PERMANOVA was significant or close to it (p <= 0.1) and the within-zone effect for time in the zone-wise PERMANOVA was significant or close to it (p <= 0.2).
Generally only one version of the SIMPER will be run (across all zones vs. zone-wise), but when the interaction term was near significance (0.05 < p < 0.1), SIMPER was run both ways.

The p-values determining the above logic are unadjusted. Due to the exploratory nature of these analyses, we did not adjust p-values for multiple comparisons

SIMPER output explanation:

The top 6 species in output are below.

“average” is the average contribution of that species to the Bray-Curtis distance between the two groups (note, this is not expressed in % and the column does not total to 1); “sd” is the standard deviation of the species’ contribution. “cumulative” is the cumulative % contribution for this species and all those above it in the table. Typically people only report species up to the one that brings “cumulative” over 0.7. “p” is a p-value for that species based on permutation tests. “mean_start” is the mean cover of that species in the starting year(s), and “mean_end” is the mean cover of the species in the last year(s) of monitoring.

Results

L-Low Marsh SIMPER results; PERMANOVA p = 0.01
	average	sd	cumulative	p	mean_start	mean_end
Spartina alterniflora	0.1834	0.1198	0.4328	0.022	57.3	39.0
Bare	0.1706	0.1245	0.8355	0.008	33.1	55.2
Wrack	0.0217	0.0474	0.8868	0.063	4.2	0.3
Dead	0.0138	0.0166	0.9193	0.885	1.8	2.1
Fucus vesiculosus	0.0128	0.0346	0.9497	0.264	0.3	2.4
Spartina patens	0.0040	0.0163	0.9591	0.504	0.8	0.0

T-Transition SIMPER results; PERMANOVA p = 0.001
	average	sd	cumulative	p	mean_start	mean_end
Spartina alterniflora	0.1711	0.1094	0.3046	0.002	34.7	57.5
Bare	0.0975	0.0920	0.4783	0.249	16.6	22.4
Spartina patens	0.0869	0.0972	0.6330	0.016	16.3	5.7
Dead	0.0679	0.1020	0.7538	0.148	12.7	5.2
Wrack	0.0508	0.0954	0.8443	0.028	9.6	1.5
Distichlis spicata	0.0337	0.0619	0.9044	0.126	4.2	3.6

H-High Marsh SIMPER results; PERMANOVA p = 0.284
None
SIMPER not run

UE-Upland Edge SIMPER results; PERMANOVA p = 0.313
None
SIMPER not run

NMDS - start/end

In this section, NMDS is performed on data from only the starting and ending years for each vegetation zone. This tab essentially illustrates the PERMANOVA results. For NMDS with all years, see the tab ‘NMDS - all years’.

Non-metric multidimensional scaling is an ordination method that preserves ranked dissimilarities between observations. Exact calculated distances are not preserved in this type of ordination. Points that are closer together on the graphs are more similar than points that are further away, so NMDS is good for seeing groupings and gradients when present. For more information, see the sources referenced below.

This NMDS used Bray-Curtis dissimilarity on the full species matrix (see ‘About’ tab for list of species included), and 3 dimensions.

Final 3-dimensional NMDS stress was 0.1368.

Rules of thumb for interpreting stress, based on the sources below, are:

For more information on NMDS:

Clarke, K. R. (1993). Non-parametric multivariate analyses of changes in community structure. Australian Journal of Ecology, 18(1), Article 1. https://doi.org/10.1111/j.1442-9993.1993.tb00438.x

Clarke, K. R., & Warwick, R. M. (2001). Change in Marine Communities: An Approach to Statistical Analysis and Interpretation, 2nd ed. - Chapter 5 focuses on NMDS.

Zuur, A. F., Ieno, E. N., & Smith, G. M. (2007). Analysing ecological data. Springer. - Chapter 15 for NMDS.

2-dimensional NMDS plot

(first two axes only)

Each small point represents a single vegetation plot at a single time point (start, open circles; or end, filled circles), as in the 3-d plot. Point color represents the plot’s vegetation zone.
Large points represent the centroid for each Vegetation Zone/Time period combination. They are labelled with the Vegetation Zone abbreviation and ‘Start’ or ‘End’. Additionally, they are colored by Vegetation Zone and shaped by ‘Start’ vs. ‘End’ time periods. Upon hover, the full Vegetation Zone name and year(s) represented will be provided.
The black lines and labels correspond to the red lines and labels in the 3d graph, and represent the loadings: coordinates of species or species groups (centroid of comprising species) specified in the Analysis_Specs worksheet of the veg-specs.xlsx file. Hovering over an arrow will make the species or group name appear more clearly.
Some identified loading factors may not appear as arrows; this is usually because all % cover values for that species or group were 0. Cover values may also have been too low to have produced species scores in the NMDS.

Contour plots

The below plots, rather than using arrows for individual species or vegetation groups, create contours for the specific values of each. Contours are labeled with % cover values and are fit as a spline-based surface using vegan::ordisurf().

Click to expand contour plots.

## Right now, only individual species and not species groups can be used in contour plots. A-Algae is not plotted here. 
## 
## Right now, only individual species and not species groups can be used in contour plots. B-Brackish is not plotted here. 
## 
## Right now, only individual species and not species groups can be used in contour plots. F-Freshwater is not plotted here. 
## 
## Right now, only individual species and not species groups can be used in contour plots. H-Halophyte is not plotted here.

## Right now, only individual species and not species groups can be used in contour plots. U-Upland is not plotted here. 
## 
## Right now, only individual species and not species groups can be used in contour plots. Unvegetated category is not plotted here.

3-d NMDS plot

This 3-d plot is interactive - you can zoom in and rotate the view. Each point represents a single vegetation plot at a single time point (start, open circles; or end, filled circles). Point color represents the plot’s vegetation zone. The red lines and labels represent the coordinates of species or species groups (centroid of comprising species) specified in the Analysis_Specs worksheet of the veg-specs.xlsx file.

Optional additional loadings

No additional loadings specified. If you would like to graph additional environmental factors on the NMDS plot, please specify them in the ‘NMDS additional loadings’ section of the ‘More_Options’ sheet in the veg-specs.xlsx file.

NMDS - all years

By default, this analysis is not run because it may take more computing power than is available to perform ordination on many years worth of data points.

The all-years NMDS was attempted. If the results are not below, it simply didn’t work with your computer.

All measurements at all veg plots (with 3+ years of data) are represented. Centroids are calculated for each zone x year combination. Plots are zoomable. Two plots are provided: the first uses fixed axis scales, to emphasize where zone centroids are relative to each other in ordination space. The second uses free axis scales, to emphasize within-zone differences between years. There may not be much difference between these visually, depending on the spread of points within each zone. Zooming works differently in each. The loadings plot below applies to both graphs (the entire NMDS).

Documentation

R Session Info; click to expand

## R version 4.4.1 (2024-06-14 ucrt)
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Site	2010	2011	2013	2014	2016	2017	2018	2019	2020	2021	2022
BC	29	30	30	30	30	30	30	30	30	30	30
GBF	39	39	39	39	39	39	39	39	39	39	39
SP	43	44	44	45	45	45	45	45	45	45	45

Site	2010	2011	2013	2014	2016	2017	2018	2019	2020	2021	2022
BC	29	30	30	30	30	30	30	30	30	30	30
GBF	39	39	39	39	39	39	39	39	39	39	39
SP	43	44	44	45	45	45	45	45	45	45	45

Veg Analysis: GRB

About this Document

Using the html file

General notes about notation, data inclusion, and reserve choices

Exploration and QA/QC

About

Ask yourself:

Missing/Removed Data

Plots/dates without samples

Plots without enough samples

Data flagged suspect or reject

Sampling Info

Samples per year

Species

Plots and Zones

Time-series - Species

By Zone

All plots combined

EMI

Summary Bar Charts

About

Questions addressed

Averaged: By Veg Zone

User-chosen species

Top 3 species by mean cover across the entire dataset

Averaged: By Site

User-chosen species

Top 3 species by mean cover across the entire dataset

Averaged: Zone within Site

User-chosen species

Top 3 species by mean cover across the entire dataset

Spatial

User-chosen species

Top 3 species by mean cover across the entire dataset

Univariate Analyses

About

Questions addressed

Statistical Model

Reserve-identified response variables:

Custom Metrics

EMI

Numerical effects

Graphs

Contrasts plot

Richness

Numerical effects

Graphs

Contrasts plot

Diversity

Numerical effects

Graphs

Contrasts plot

Unvegetated category

Numerical effects

Graphs

Contrasts plot

Spartina alterniflora

Numerical effects

Graphs

Contrasts plot

Spartina patens

Numerical effects

Graphs

Contrasts plot

H-Halophyte

Numerical effects

Graphs

Contrasts plot

AlgaeEtc.

Numerical effects

Graphs

Contrasts plot

Sppa.Disp.Juge

Numerical effects

Graphs

Contrasts plot

Multivariate Analyses

About

Questions and statistical methods

Reserve output choices

Site	2010	2011	2013	2014	2016	2017	2018	2019	2020	2021	2022
BC	29	30	30	30	30	30	30	30	30	30	30
GBF	39	39	39	39	39	39	39	39	39	39	39
SP	43	44	44	45	45	45	45	45	45	45	45